{ "_id": "6a366ae13efcd9bda4408dbd", "Package": "RefBasedMI", "Title": "Reference-Based Imputation for Longitudinal Clinical Trials with\nProtocol Deviation", "Version": "0.2.0", "Authors@R": "c(person(given = \"Kevin\",\nfamily = \"McGrath\",\nrole = \"aut\",\nemail = \"kkevinmcgrath@yahoo.co.uk\"),\nperson(given = \"Matteo\",\nfamily = \"Quartagno\",\nrole = \"cre\",\nemail = \"m.quartagno@ucl.ac.uk\"))", "Description": "Imputation of missing numerical outcomes for a\nlongitudinal trial with protocol deviations. The package uses\ndistinct treatment arm-based assumptions for the unobserved\ndata, following the general algorithm of Carpenter, Roger, and\nKenward (2013) , and the\ncausal model of White, Royes and Best (2020)\n. Sensitivity analyses to\ndepartures from these assumptions can be done by the Delta\nmethod of Roger. The program uses the same algorithm as the\n'mimix' 'Stata' package written by Suzie Cro, with additional\ncoding for the causal model and delta method. The\nreference-based methods are jump to reference (J2R), copy\nincrements in reference (CIR), copy reference (CR), and the\ncausal model, all of which must specify the reference treatment\narm. Other methods are missing at random (MAR) and the last\nmean carried forward (LMCF). 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